RegiStax5

Free image processing
software

Trapping noise with Gaussian wavelets

(by Cor Berrevoets )

Introduction

Sometimes
you find that when using wavelets you get to see more noise
instead of
details when enhancing the image. This noise is often most visible in
wavelet-layer 1 but can often also persist in other layers.
RegiStax wavelets allow you to "trap" part of the noise so the effects
of
the noise do not show up in the higher layers.

Using GaussianYouwill
need to use the Gaussian wavelets as they allow more control of each
wavelet-layer. The gaussian filters are most of the time (also when you
do not have much noise) the best way to enhance image details with most
user control.

HOW ?Firstmake
sure all the Gaussian filters are set at 0.1 (the default). Then
uncheck layer 1 (this will be the layer we are trying to trap the noise
into) or set the slider of layer 1 to 0.0). Unchecking
a layer makes the details in that layer invisible.

Now
move the slider of layer 2 upward until you see the noise appearing in
the image. You might even try to reduce the filter-size of layer 2 but
thats not necessary (figure 1).

When
the noise is clearly visible we will try to trap the noise into layer 1
by
enlarging the gaussian filter of layer 1. Just increase the gaussian
filtersize using the up/down control next to the filtervalue. Do this
step by step until you see the noise gradually disappearing. The
figures below (figure 2 and 3) show the effect of simply increasing the
filtersize of layer 1. Be aware that as a consequence of increasing the
filtersize of layer 1 you might loose details. Figure 3 in the example
below clearly shows less details than Figure 2. As always every
stacking-result will demand carefull tuning of wavelets to get the most
out of your images. The settings I have used in the example below are
therefore not by any chance "golden settings". You will need to
experiment yourself to find out what kind of wavelet-settings your
images need.

Cor Berrevoets

Figure 1: visible noise
in the image

Figure 2: After
deselecting layer 1 and increasing the filtersize of layer 1 from 0.10
to 0.15

Figure 3:
After increasing the filtersize of layer 1 from 0.15 to 0.20